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Privacy Preserving Machine Learning Jobs in Massachusetts

Vrtx

Director, AI Governance & Policy

Boston, MA · On-site

This role will lead the governance of generative AI, agentic AI, machine learning, and AI-enabled ... Partner with Legal, Privacy, Compliance, Quality, Information Security, Data Governance, and Data ...

Accenture

Senior Data Scientist

Boston, MA · On-site

Develop supervised and unsupervised machine learning solutions, including classification ... Experience with AI governance, Responsible AI, model risk, data ethics, privacy, security ...

New

Chewy

Data Scientist I

Boston, MA · On-site

$117K - $163K/yr

Develop machine learning applications according to requirements; design, code, test, deploy and ... To access Chewy's California CPRA Job Applicant Privacy Policy, please click here.

Meta

Research Scientist Intern, AI Alignment

Boston, MA

$7.6K - $12K/mo

... machine learning, reinforcement learning, computational statistics, applied mathematics and security/privacy. Our interns have an opportunity to make core algorithmic advances and apply their ideas ...

OneStudyTeam

Senior Data Scientist

Boston, MA · On-site +1

$140K - $190K/yr

... machine learning algorithms to improve patient enrollment and trial management. You'll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while ...

Azenta

Senior Product Data Analyst

Burlington, MA

Identify opportunities to apply Artificial Intelligence (AI), Machine Learning (ML), automation ... Promote responsible AI practices, including explainability, human oversight, data privacy, security ...

Azenta

Senior Product Data Analyst

Burlington, MA · On-site

Identify opportunities to apply Artificial Intelligence (AI), Machine Learning (ML), automation ... Promote responsible AI practices, including explainability, human oversight, data privacy, security ...

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Massachusetts

Privacy Preserving Machine Learning information

What are some common challenges faced by professionals working in privacy preserving machine learning roles?

Professionals in Privacy Preserving Machine Learning often encounter challenges such as balancing model accuracy with strict privacy requirements, selecting appropriate privacy-preserving techniques (like differential privacy or federated learning), and ensuring compliance with evolving data protection regulations. Collaborative projects may also involve coordinating with legal, data security, and software engineering teams to implement robust solutions. Additionally, staying updated with the latest research and adapting to new threats or vulnerabilities is a continuous part of the role.

What is the difference between Privacy Preserving Machine Learning vs Data Scientist?

AspectPrivacy Preserving Machine LearningData Scientist
Required CredentialsTypically requires knowledge of machine learning, data privacy, and security certificationsRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentWorks in research, development, and implementation of privacy-focused ML models, often in tech or finance sectorsAnalyzes data, builds models, and provides insights across various industries including marketing, finance, and healthcare
Employer & Industry UsageUsed by organizations prioritizing data privacy, such as healthcare, finance, and tech companiesEmployed across diverse sectors for data analysis, predictive modeling, and decision support

Privacy Preserving Machine Learning focuses on developing models that protect data privacy during training and inference, while Data Scientists analyze and interpret data to generate insights. Both roles require strong analytical skills, but Privacy Preserving Machine Learning emphasizes security and privacy techniques, whereas Data Scientists focus on data analysis and modeling.

What is privacy preserving machine learning?

Privacy preserving machine learning refers to techniques and methods that allow data analysis and model training while protecting sensitive information. This field focuses on ensuring that personal or confidential data is not exposed or compromised during the development and deployment of machine learning models. Approaches such as federated learning, differential privacy, and homomorphic encryption are commonly used. These methods enable organizations to leverage data for insights and predictions without violating privacy regulations or risking data breaches. Privacy preserving machine learning is especially important in industries like healthcare, finance, and any sector handling personal data.

What are the key skills and qualifications needed to thrive as a privacy preserving machine learning engineer?

To thrive as a Privacy Preserving Machine Learning Engineer, you need a strong background in machine learning, data privacy techniques (such as differential privacy or federated learning), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow Privacy, PySyft, and privacy-enhancing technologies, along with certifications in data security or privacy, are often required. Strong problem-solving abilities, meticulous attention to detail, and the ability to communicate complex technical concepts clearly set top professionals apart. These skills ensure the development of robust machine learning models that protect sensitive data while delivering valuable insights, maintaining compliance and trust.
What are popular job titles related to Privacy Preserving Machine Learning jobs in Massachusetts? For Privacy Preserving Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Privacy Preserving Machine Learning jobs in Massachusetts look for? The top searched job categories for Privacy Preserving Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Privacy Preserving Machine Learning jobs? Cities in Massachusetts with the most Privacy Preserving Machine Learning job openings:
Privacy Preserving Machine Learning jobs near you
Infographic showing various Privacy Preserving Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Director, AI Governance & Policy

Vrtx

Boston, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Job description

Job Description

General / Position Summary

Vertex is entering a transformative phase in its AI journey, where responsible, trusted, and compliant AI is foundational to accelerating innovation, improving patient outcomes, and enabling enterprise-wide productivity. We are seeking a visionary and execution-focusedDirector, AI Governance & Policyto lead Vertex's enterprise AI Governance program and establish the policies, operating models, and technology platforms that enable safe, ethical, and business-enabling adoption of AI across the company.

This role will lead the governance of generative AI, agentic AI, machine learning, and AI-enabled business solutions. The Director will oversee AI policy development, risk management, governance operations, technology platforms, regulatory compliance, and Responsible AI practices while partnering closely with Data Governance, Information Security, Privacy, Legal, Compliance, Quality, and business stakeholders. The role will ensure AI innovation scales responsibly while balancing risk management with business value realization.

Key Duties & Responsibilities

Strategic Leadership

  • Define and execute the enterprise AI Governance strategy aligned with Vertex's business, data, and AI priorities.
  • Establish and evolve Vertex's Responsible AI framework, policies, standards, and governance operating model.
  • Serve as a trusted advisor to senior leaders on AI governance, risk, compliance, and emerging AI technologies.
  • Monitor industry trends, regulations, and best practices to continuously mature Vertex's AI governance capabilities.

AI Governance, Risk & Platform Ownership

  • Lead enterprise AI governance processes, including AI intake, review, approval, monitoring, and lifecycle management.
  • Define and maintain AI risk management frameworks, controls, and governance standards aligned with regulatory and industry expectations.
  • Own the strategy, roadmap, implementation, and operation of the enterprise AI Governance platform, including AI inventories, policy management, risk assessments, workflow automation, monitoring, reporting, and compliance evidence management.
  • Establish governance approaches for emerging AI technologies including generative AI, AI agents, knowledge graphs, and retrieval-augmented generation (RAG) solutions.
  • Ensure appropriate oversight, documentation, auditability, and accountability for AI systems, models, and agents deployed across the enterprise.

Responsible AI, Compliance & Cross-functional Leadership

  • Develop and maintain enterprise AI policies, standards, and guidelines supporting both regulated and non-regulated use cases.
  • Ensure compliance with evolving AI regulations, industry frameworks, and internal governance requirements.
  • Partner with Legal, Privacy, Compliance, Quality, Information Security, Data Governance, and Data & AI Product teams to embed governance-by-design into AI solutions.
  • Lead the AI Policy Council and AI Review process, ensuring effective governance, decision-making, and stakeholder alignment across the enterprise.

Culture, Training & Enablement

  • Promote AI literacy and Responsible AI adoption through training, communications, and stakeholder engagement programs.
  • Build a culture that enables innovation while maintaining trust, transparency, compliance, and accountability.

Knowledge & Skills

  • Deep expertise in AI governance, Responsible AI, risk management, and enterprise governance frameworks.
  • Strong understanding of generative AI, large language models (LLMs), AI agents, machine learning, knowledge graphs, and RAG architectures.
  • Experience designing and operating enterprise AI governance programs, policies, operating models, and governance technology platforms.
  • Knowledge of AI-related regulatory requirements and standards, including FDA, EMA, EU AI Act, HIPAA, GDPR, and GxP environments.
  • Strong understanding of data governance, privacy, security, and enterprise technology controls.
  • Proven ability to influence senior stakeholders, lead cross-functional initiatives, and drive organizational change in a matrixed environment.
  • Excellent communication, stakeholder management, and strategic leadership skills.

Education & Experience

  • Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Law, Public Policy, or a related field required.
  • Advanced degree (MBA, Master's, JD, or equivalent experience) preferred.
  • 10+ years of experience in technology, governance, risk, compliance, data management, AI, or related disciplines.
  • 5+ years of experience leading enterprise governance, risk management, compliance, AI governance, or technology platform programs.
  • Experience owning or managing governance, risk, compliance, workflow, or policy management platforms strongly preferred.
  • Experience in biopharmaceutical, healthcare, or other highly regulated industries strongly preferred.
  • Professional certifications such as AIGP, CIPP, CRISC, CISM, ISO 42001, or related credentials are preferred.

#LI-HYBRID

Pay Range:

$184,000 - $276,000

Disclosure Statement:

The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

Flex Designation:

Hybrid-Eligible Or On-Site Eligible

Flex Eligibility Status:

In this Hybrid-Eligible role, you can choose to be designated as:
1. Hybrid: work remotely up to two days per week; or select
2. On-Site: work five days per week on-site with ad hoc flexibility.

Note: The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.

#LI-Hybrid

Company Information

Vertex is a global biotechnology company that invests in scientific innovation.

Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com

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